Bayesian approaches to supervised learning use priors on the classifier parameters. However, few priors aim at achieving "sparse" classifiers, where irrelevant/redundant...
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
A pervasive problem in large relational databases is identity uncertainty which occurs when multiple entries in a database refer to the same underlying entity in the world. Relati...
— Category Ranking is a variant of the multi-label classification problem, in which, rather than performing a (hard) assignment to an object of categories from a predefined set...
: In recent years, market forecasting by machine learning methods has been flourishing. Most existing works use a past market data set, because they assume that each trader’s in...